FREEDM Tech Webinar Series: A GAN-based Super-Resolution Method for Generating High-Resolution Load Profiles
Title: A GAN-based Super-Resolution Method for Generating High-Resolution Load Profiles
Presenter: Lidong Song, Ph.D. Student
It is a common practice for utilities to down-sample smart meter measurements from high resolution (e.g. 1-min or 1-sec) to low resolution (e.g. 15-, 30- or 60-min) to lower the data transmission and storage cost. However, down-sampling can remove high-frequency components from time-series load profiles, making them unsuitable for in-depth studies such as quasi-static power flow analysis or non-intrusive load monitoring (NILM). Thus, we propose a Generative Adversarial Network (GAN) based load profile super-resolution (LPSR) framework for restoring high-frequency components lost through the smoothing effect of the down-sampling process, which outperforms the traditional Mean Square Error (MSE) based super-resolution methods.
This is a virtual event. Attendees must register to receive the meeting link.
January 20, 2022
11:00 AM - 12:00 PM